Women in STEM

Women have every opportunity to excel in STEM (Science, Technology, Engineering, and Math) career fields. The CloudQuant team has worked with several talented women in our careers and hope to encourage other women to join us in the world of Financial Technology and Algorithmic Trading.

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Sonal Gupta is an MBA graduate student at Case Western Reserve University in Ohio. She has five years experience in leading software development teams, product development and consulting engagements. She has the ability to analyze large volumes of data and generating actionable insights. We asked her what her experience has been like as a female in data science and invite you to read her response below.

https://info.cloudquant.com/wp-content/uploads/sonal.jpg12801280Tayloe Draughonhttps://info.cloudquant.com/wp-content/uploads/cloudquant_final_w_horiz-300x100.pngTayloe Draughon2018-07-13 18:05:052018-07-13 18:14:01What is it like to be a female in Data Science?

“It’s exciting to see the growing number of women in Science, Technology, Engineering and Math (STEM); my advice is to not be afraid to jump in headfirst,” said Sarah Leonard, graduate student at the University of Chicago. “It is a difficult field but also lucrative and rapidly growing.”
Leonard sat down with CloudQuant to talk about her experiences in data science, her insight as a female in a male dominated world, and the intensive process it took to find her dream job.

The first book I got was “Hello World”. The book intimidated me, because I saw programming as a superpower, something only my dad was capable enough to do. I tried to learn it, but I just got bored very quickly. My dad, still persistent, decided it was time to try programming something we loved.

TD Sequential is a technical indicator for stock trading developed by Thomas R. DeMark in the 1990s. It uses bar plot of stocks to generate trading signals. ... Several elements could be modified in this strategy. Whether to include the countdown stage, the choice of the number of bars in the setup stage and countdown stage, the parameters that help to decide when to exit and the size of the trade will affect strategy performance. In addition, we could use information other than price to decide whether the signal should be traded.

The thoughts and opinions on this site do not represent investment recommendations by CloudQuant or Kershner Trading Group. Securities, charts, illustrations and other information contained herein are provided to assist crowd researchers in their efforts to develop algorithmic trading strategies for backtesting on CloudQuant.